Topics in many-body theory of nuclear effective interactions

博夫 熊谷

Hagai T. Attias

E. Cenni, Gary P. Dillon, Paolo Saracco

Byron K. Jennings, A. Schwenk

Over the past five years there have been profound advances in nuclear physics based on effective field theory and the renormalization group. In this review, we summarize these advances and discuss how they impact our understanding of nuclear systems and experiments that seek to unravel their unknowns. We discuss future opportunities and focus on modern topics in low-energy nuclear physics, with special attention on the strong connections to many-body atomic and condensed-matter physics, as well as to astrophysics. This makes it an exciting era for nuclear physics. PACS Nos.: 21.60.–n, 21.30.Fe

Michael W. Kirson, Francesco Calogero

Nawar Ismail

This thesis contains two topics related to strongly interacting neutron matter. The first considers the effective mass, described in Landau Fermi liquid theory, which aims to capture many-body physics in terms of a single parameter. Monte Carlo algorithms were used to determine energies for finite particle simulations. Studying the deviations from the thermodynamic limit for the non-interacting gas allows for claims about the macroscopic scale. Following this systematic investigation, the density dependence was determined to be less than one for the considered densities. The second topic focuses on machine learning algorithms which have proliferated into many fields, with an emerging popularity in nuclear physics. These algorithms work by learning patterns found in datasets to develop their predictive power. After identifying and resolving issues introduced by a small dataset, they were used to extrapolate finite calculations to zero effective-range in the thermodynamic limit, which best approximates neutron matter.